Overview

Dataset statistics

Number of variables58
Number of observations1020495
Missing cells8852
Missing cells (%)< 0.1%
Duplicate rows1384
Duplicate rows (%)0.1%
Total size in memory451.6 MiB
Average record size in memory464.0 B

Variable types

Numeric6
Categorical52

Alerts

multiple_values has constant value "0"Constant
16 has constant value "0"Constant
ages_16_ has constant value "0"Constant
all_ages has constant value "0"Constant
not rated has constant value "0"Constant
not_rate has constant value "0"Constant
Dataset has 1384 (0.1%) duplicate rowsDuplicates
id has a high cardinality: 3788 distinct valuesHigh cardinality
title has a high cardinality: 3756 distinct valuesHigh cardinality
year is highly overall correlated with gene autry and 1 other fieldsHigh correlation
duration_int is highly overall correlated with duration_typeHigh correlation
diftiempo is highly overall correlated with yearHigh correlation
duration_type is highly overall correlated with duration_intHigh correlation
amazon is highly overall correlated with united states and 3 other fieldsHigh correlation
netflix is highly overall correlated with tv-ma and 1 other fieldsHigh correlation
gene autry is highly overall correlated with yearHigh correlation
united states is highly overall correlated with amazonHigh correlation
13+ is highly overall correlated with amazonHigh correlation
all is highly overall correlated with kidsHigh correlation
tv-ma is highly overall correlated with amazon and 1 other fieldsHigh correlation
tv-y is highly overall correlated with kidsHigh correlation
kids is highly overall correlated with all and 1 other fieldsHigh correlation
id is uniformly distributedUniform
diftiempo has 27412 (2.7%) zerosZeros

Reproduction

Analysis started2023-02-19 14:48:54.342758
Analysis finished2023-02-19 15:11:32.538827
Duration22 minutes and 38.2 seconds
Software versionpandas-profiling vv3.5.0
Download configurationconfig.json

Variables

userId
Real number (ℝ)

Distinct10000
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89749.866
Minimum12
Maximum270887
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.8 MiB
2023-02-19T12:11:33.105311image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile5723
Q128501
median56456
Q3116975
95-th percentile265335
Maximum270887
Range270875
Interquartile range (IQR)88474

Descriptive statistics

Standard deviation86921.235
Coefficient of variation (CV)0.96848318
Kurtosis-0.07855996
Mean89749.866
Median Absolute Deviation (MAD)35356
Skewness1.1789965
Sum9.158929 × 1010
Variance7.5553012 × 109
MonotonicityNot monotonic
2023-02-19T12:11:33.397532image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45811 3120
 
0.3%
8659 1670
 
0.2%
270123 1288
 
0.1%
70648 900
 
0.1%
74275 849
 
0.1%
24025 837
 
0.1%
41190 811
 
0.1%
65469 798
 
0.1%
59449 781
 
0.1%
59554 765
 
0.1%
Other values (9990) 1008676
98.8%
ValueCountFrequency (%)
12 58
< 0.1%
20 53
< 0.1%
24 97
< 0.1%
43 48
 
< 0.1%
46 129
< 0.1%
47 50
 
< 0.1%
49 72
< 0.1%
56 47
 
< 0.1%
62 79
< 0.1%
65 58
< 0.1%
ValueCountFrequency (%)
270887 426
< 0.1%
270879 71
 
< 0.1%
270871 47
 
< 0.1%
270859 51
 
< 0.1%
270828 111
 
< 0.1%
270807 89
 
< 0.1%
270776 52
 
< 0.1%
270769 135
 
< 0.1%
270763 58
 
< 0.1%
270759 79
 
< 0.1%

score
Real number (ℝ)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.412441
Minimum0.5
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.8 MiB
2023-02-19T12:11:33.737578image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile1.5
Q13
median3.5
Q34
95-th percentile5
Maximum5
Range4.5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0383697
Coefficient of variation (CV)0.30428943
Kurtosis0.1581837
Mean3.412441
Median Absolute Deviation (MAD)0.5
Skewness-0.63197174
Sum3482379
Variance1.0782117
MonotonicityNot monotonic
2023-02-19T12:11:33.981964image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
4 263899
25.9%
3 210184
20.6%
3.5 150031
14.7%
5 104160
 
10.2%
4.5 80596
 
7.9%
2 77395
 
7.6%
2.5 64757
 
6.3%
1 33559
 
3.3%
1.5 19442
 
1.9%
0.5 16472
 
1.6%
ValueCountFrequency (%)
0.5 16472
 
1.6%
1 33559
 
3.3%
1.5 19442
 
1.9%
2 77395
 
7.6%
2.5 64757
 
6.3%
3 210184
20.6%
3.5 150031
14.7%
4 263899
25.9%
4.5 80596
 
7.9%
5 104160
 
10.2%
ValueCountFrequency (%)
5 104160
 
10.2%
4.5 80596
 
7.9%
4 263899
25.9%
3.5 150031
14.7%
3 210184
20.6%
2.5 64757
 
6.3%
2 77395
 
7.6%
1.5 19442
 
1.9%
1 33559
 
3.3%
0.5 16472
 
1.6%

id
Categorical

HIGH CARDINALITY
UNIFORM

Distinct3788
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
hs735
 
323
ns6499
 
315
ns1914
 
313
hs911
 
312
ns5743
 
311
Other values (3783)
1018921 

Length

Max length6
Median length6
Mean length5.8052337
Min length3

Characters and Unicode

Total characters5924212
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowas3004
2nd rowas3004
3rd rowas3004
4th rowas3004
5th rowas3004

Common Values

ValueCountFrequency (%)
hs735 323
 
< 0.1%
ns6499 315
 
< 0.1%
ns1914 313
 
< 0.1%
hs911 312
 
< 0.1%
ns5743 311
 
< 0.1%
ns3777 310
 
< 0.1%
ns4179 310
 
< 0.1%
ns3475 310
 
< 0.1%
ns2835 310
 
< 0.1%
as2920 309
 
< 0.1%
Other values (3778) 1017372
99.7%

Length

2023-02-19T12:11:34.262219image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
hs735 323
 
< 0.1%
ns6499 315
 
< 0.1%
ns1914 313
 
< 0.1%
hs911 312
 
< 0.1%
ns5743 311
 
< 0.1%
ns3777 310
 
< 0.1%
ns4179 310
 
< 0.1%
ns3475 310
 
< 0.1%
ns2835 310
 
< 0.1%
as2920 309
 
< 0.1%
Other values (3778) 1017372
99.7%

Most occurring characters

ValueCountFrequency (%)
s 1020495
17.2%
1 438735
 
7.4%
2 436596
 
7.4%
a 426951
 
7.2%
3 412167
 
7.0%
5 406494
 
6.9%
n 398670
 
6.7%
4 398203
 
6.7%
6 397572
 
6.7%
7 386847
 
6.5%
Other values (5) 1201482
20.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3883222
65.5%
Lowercase Letter 2040990
34.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 438735
11.3%
2 436596
11.2%
3 412167
10.6%
5 406494
10.5%
4 398203
10.3%
6 397572
10.2%
7 386847
10.0%
8 380073
9.8%
9 320863
8.3%
0 305672
7.9%
Lowercase Letter
ValueCountFrequency (%)
s 1020495
50.0%
a 426951
20.9%
n 398670
 
19.5%
h 131973
 
6.5%
d 62901
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3883222
65.5%
Latin 2040990
34.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 438735
11.3%
2 436596
11.2%
3 412167
10.6%
5 406494
10.5%
4 398203
10.3%
6 397572
10.2%
7 386847
10.0%
8 380073
9.8%
9 320863
8.3%
0 305672
7.9%
Latin
ValueCountFrequency (%)
s 1020495
50.0%
a 426951
20.9%
n 398670
 
19.5%
h 131973
 
6.5%
d 62901
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5924212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 1020495
17.2%
1 438735
 
7.4%
2 436596
 
7.4%
a 426951
 
7.2%
3 412167
 
7.0%
5 406494
 
6.9%
n 398670
 
6.7%
4 398203
 
6.7%
6 397572
 
6.7%
7 386847
 
6.5%
Other values (5) 1201482
20.3%

title
Categorical

Distinct3756
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
moesha
 
825
xx
 
576
bordertown
 
576
money for nothing
 
575
crshd
 
564
Other values (3751)
1017379 

Length

Max length104
Median length70
Mean length18.642554
Min length1

Characters and Unicode

Total characters19024633
Distinct characters100
Distinct categories17 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowbookaboo uk
2nd rowbookaboo uk
3rd rowbookaboo uk
4th rowbookaboo uk
5th rowbookaboo uk

Common Values

ValueCountFrequency (%)
moesha 825
 
0.1%
xx 576
 
0.1%
bordertown 576
 
0.1%
money for nothing 575
 
0.1%
crshd 564
 
0.1%
good kisser 563
 
0.1%
hunt to kill 561
 
0.1%
blue exorcist 553
 
0.1%
the confirmation 551
 
0.1%
chance 550
 
0.1%
Other values (3746) 1014601
99.4%

Length

2023-02-19T12:11:34.699044image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the 263178
 
7.9%
of 86189
 
2.6%
a 45374
 
1.4%
42530
 
1.3%
and 33865
 
1.0%
in 28917
 
0.9%
to 22264
 
0.7%
with 19243
 
0.6%
for 17620
 
0.5%
love 15925
 
0.5%
Other values (5196) 2741032
82.7%

Most occurring characters

ValueCountFrequency (%)
2295642
 
12.1%
e 1818235
 
9.6%
a 1490648
 
7.8%
t 1224063
 
6.4%
o 1157881
 
6.1%
i 1142679
 
6.0%
r 1114082
 
5.9%
n 1054983
 
5.5%
s 1043185
 
5.5%
l 796327
 
4.2%
Other values (90) 5886908
30.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16163475
85.0%
Space Separator 2295642
 
12.1%
Other Punctuation 294836
 
1.5%
Decimal Number 157117
 
0.8%
Dash Punctuation 44415
 
0.2%
Open Punctuation 28098
 
0.1%
Close Punctuation 28098
 
0.1%
Math Symbol 3545
 
< 0.1%
Other Letter 2897
 
< 0.1%
Final Punctuation 2657
 
< 0.1%
Other values (7) 3853
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1818235
11.2%
a 1490648
 
9.2%
t 1224063
 
7.6%
o 1157881
 
7.2%
i 1142679
 
7.1%
r 1114082
 
6.9%
n 1054983
 
6.5%
s 1043185
 
6.5%
l 796327
 
4.9%
h 782601
 
4.8%
Other values (34) 4538791
28.1%
Other Punctuation
ValueCountFrequency (%)
: 139590
47.3%
' 56709
19.2%
. 30359
 
10.3%
, 19454
 
6.6%
& 17313
 
5.9%
! 16666
 
5.7%
? 5710
 
1.9%
/ 3013
 
1.0%
* 2450
 
0.8%
# 1620
 
0.5%
Other values (5) 1952
 
0.7%
Decimal Number
ValueCountFrequency (%)
2 31854
20.3%
1 30999
19.7%
0 29882
19.0%
3 13531
8.6%
9 12720
 
8.1%
4 11615
 
7.4%
5 11118
 
7.1%
6 6242
 
4.0%
8 5331
 
3.4%
7 3825
 
2.4%
Other Letter
ValueCountFrequency (%)
526
18.2%
526
18.2%
264
9.1%
264
9.1%
264
9.1%
264
9.1%
263
9.1%
263
9.1%
263
9.1%
Math Symbol
ValueCountFrequency (%)
+ 1365
38.5%
| 1334
37.6%
~ 558
15.7%
288
 
8.1%
Dash Punctuation
ValueCountFrequency (%)
- 44132
99.4%
283
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 27291
97.1%
[ 807
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 27291
97.1%
] 807
 
2.9%
Final Punctuation
ValueCountFrequency (%)
2379
89.5%
278
 
10.5%
Other Number
ValueCountFrequency (%)
½ 288
51.2%
² 275
48.8%
Initial Punctuation
ValueCountFrequency (%)
280
50.2%
278
49.8%
Space Separator
ValueCountFrequency (%)
2295642
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1144
100.0%
Spacing Mark
ValueCountFrequency (%)
526
100.0%
Nonspacing Mark
ValueCountFrequency (%)
526
100.0%
Other Symbol
ValueCountFrequency (%)
270
100.0%
Format
ValueCountFrequency (%)
266
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16163475
85.0%
Common 2857209
 
15.0%
Tamil 2893
 
< 0.1%
Han 1056
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2295642
80.3%
: 139590
 
4.9%
' 56709
 
2.0%
- 44132
 
1.5%
2 31854
 
1.1%
1 30999
 
1.1%
. 30359
 
1.1%
0 29882
 
1.0%
( 27291
 
1.0%
) 27291
 
1.0%
Other values (35) 143460
 
5.0%
Latin
ValueCountFrequency (%)
e 1818235
11.2%
a 1490648
 
9.2%
t 1224063
 
7.6%
o 1157881
 
7.2%
i 1142679
 
7.1%
r 1114082
 
6.9%
n 1054983
 
6.5%
s 1043185
 
6.5%
l 796327
 
4.9%
h 782601
 
4.8%
Other values (34) 4538791
28.1%
Tamil
ValueCountFrequency (%)
526
18.2%
526
18.2%
526
18.2%
526
18.2%
263
9.1%
263
9.1%
263
9.1%
Han
ValueCountFrequency (%)
264
25.0%
264
25.0%
264
25.0%
264
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19001602
99.9%
None 14450
 
0.1%
Punctuation 4074
 
< 0.1%
Tamil 2893
 
< 0.1%
CJK 1056
 
< 0.1%
Arrows 288
 
< 0.1%
Specials 270
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2295642
 
12.1%
e 1818235
 
9.6%
a 1490648
 
7.8%
t 1224063
 
6.4%
o 1157881
 
6.1%
i 1142679
 
6.0%
r 1114082
 
5.9%
n 1054983
 
5.6%
s 1043185
 
5.5%
l 796327
 
4.2%
Other values (49) 5863877
30.9%
None
ValueCountFrequency (%)
é 4578
31.7%
ñ 2605
18.0%
ó 1348
 
9.3%
ü 572
 
4.0%
ş 550
 
3.8%
í 524
 
3.6%
á 524
 
3.6%
½ 288
 
2.0%
ø 285
 
2.0%
æ 283
 
2.0%
Other values (11) 2893
20.0%
Punctuation
ValueCountFrequency (%)
2379
58.4%
310
 
7.6%
283
 
6.9%
280
 
6.9%
278
 
6.8%
278
 
6.8%
266
 
6.5%
Tamil
ValueCountFrequency (%)
526
18.2%
526
18.2%
526
18.2%
526
18.2%
263
9.1%
263
9.1%
263
9.1%
Arrows
ValueCountFrequency (%)
288
100.0%
Specials
ValueCountFrequency (%)
270
100.0%
CJK
ValueCountFrequency (%)
264
25.0%
264
25.0%
264
25.0%
264
25.0%

year
Real number (ℝ)

Distinct90
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011.1162
Minimum1923
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.8 MiB
2023-02-19T12:11:35.090001image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum1923
5-th percentile1980
Q12010
median2016
Q32019
95-th percentile2021
Maximum2021
Range98
Interquartile range (IQR)9

Descriptive statistics

Standard deviation14.795163
Coefficient of variation (CV)0.007356692
Kurtosis9.8871669
Mean2011.1162
Median Absolute Deviation (MAD)4
Skewness-2.9838129
Sum2.052334 × 109
Variance218.89684
MonotonicityNot monotonic
2023-02-19T12:11:35.439629image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019 108615
 
10.6%
2020 107788
 
10.6%
2021 106175
 
10.4%
2017 88635
 
8.7%
2018 88092
 
8.6%
2016 69136
 
6.8%
2015 56650
 
5.6%
2014 41724
 
4.1%
2013 33735
 
3.3%
2012 32435
 
3.2%
Other values (80) 287510
28.2%
ValueCountFrequency (%)
1923 266
 
< 0.1%
1925 252
 
< 0.1%
1932 809
 
0.1%
1934 267
 
< 0.1%
1935 1354
0.1%
1936 2138
0.2%
1937 800
 
0.1%
1938 813
 
0.1%
1939 829
 
0.1%
1940 1098
0.1%
ValueCountFrequency (%)
2021 106175
10.4%
2020 107788
10.6%
2019 108615
10.6%
2018 88092
8.6%
2017 88635
8.7%
2016 69136
6.8%
2015 56650
5.6%
2014 41724
 
4.1%
2013 33735
 
3.3%
2012 32435
 
3.2%

duration_int
Real number (ℝ)

Distinct189
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.920664
Minimum0
Maximum541
Zeros8852
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size7.8 MiB
2023-02-19T12:11:35.795676image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median83
Q3102
95-th percentile137
Maximum541
Range541
Interquartile range (IQR)99

Descriptive statistics

Standard deviation52.222182
Coefficient of variation (CV)0.79219746
Kurtosis6.5334254
Mean65.920664
Median Absolute Deviation (MAD)33
Skewness0.80032389
Sum67271708
Variance2727.1563
MonotonicityNot monotonic
2023-02-19T12:11:36.142748image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 189780
 
18.6%
2 45187
 
4.4%
3 27614
 
2.7%
91 19006
 
1.9%
90 19005
 
1.9%
93 18339
 
1.8%
92 16002
 
1.6%
88 15978
 
1.6%
4 15558
 
1.5%
97 15545
 
1.5%
Other values (179) 638481
62.6%
ValueCountFrequency (%)
0 8852
 
0.9%
1 189780
18.6%
2 45187
 
4.4%
3 27614
 
2.7%
4 15558
 
1.5%
5 11514
 
1.1%
6 7799
 
0.8%
7 5305
 
0.5%
8 3227
 
0.3%
9 3675
 
0.4%
ValueCountFrequency (%)
541 528
0.1%
540 526
0.1%
480 264
< 0.1%
240 284
< 0.1%
237 255
< 0.1%
209 279
< 0.1%
201 268
< 0.1%
192 255
< 0.1%
190 548
0.1%
185 259
< 0.1%

duration_type
Categorical

Distinct2
Distinct (%)< 0.1%
Missing8852
Missing (%)0.9%
Memory size7.8 MiB
min
706297 
season
305346 

Length

Max length6
Median length3
Mean length3.9054953
Min length3

Characters and Unicode

Total characters3950967
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowseason
2nd rowseason
3rd rowseason
4th rowseason
5th rowseason

Common Values

ValueCountFrequency (%)
min 706297
69.2%
season 305346
29.9%
(Missing) 8852
 
0.9%

Length

2023-02-19T12:11:36.427985image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:36.741637image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
min 706297
69.8%
season 305346
30.2%

Most occurring characters

ValueCountFrequency (%)
n 1011643
25.6%
m 706297
17.9%
i 706297
17.9%
s 610692
15.5%
e 305346
 
7.7%
a 305346
 
7.7%
o 305346
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3950967
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1011643
25.6%
m 706297
17.9%
i 706297
17.9%
s 610692
15.5%
e 305346
 
7.7%
a 305346
 
7.7%
o 305346
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 3950967
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1011643
25.6%
m 706297
17.9%
i 706297
17.9%
s 610692
15.5%
e 305346
 
7.7%
a 305346
 
7.7%
o 305346
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3950967
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 1011643
25.6%
m 706297
17.9%
i 706297
17.9%
s 610692
15.5%
e 305346
 
7.7%
a 305346
 
7.7%
o 305346
 
7.7%

scored
Real number (ℝ)

Distinct34
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.532955
Minimum3.38
Maximum3.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.8 MiB
2023-02-19T12:11:36.993499image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum3.38
5-th percentile3.46
Q13.5
median3.53
Q33.56
95-th percentile3.61
Maximum3.72
Range0.34
Interquartile range (IQR)0.06

Descriptive statistics

Standard deviation0.04603165
Coefficient of variation (CV)0.013029221
Kurtosis-0.096849931
Mean3.532955
Median Absolute Deviation (MAD)0.03
Skewness-0.0030323729
Sum3605363
Variance0.0021189128
MonotonicityNot monotonic
2023-02-19T12:11:37.281697image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
3.52 91557
 
9.0%
3.55 88720
 
8.7%
3.54 88001
 
8.6%
3.53 81302
 
8.0%
3.5 72743
 
7.1%
3.56 70906
 
6.9%
3.51 70160
 
6.9%
3.57 66636
 
6.5%
3.49 49433
 
4.8%
3.58 48063
 
4.7%
Other values (24) 292974
28.7%
ValueCountFrequency (%)
3.38 281
 
< 0.1%
3.39 265
 
< 0.1%
3.4 1588
 
0.2%
3.41 1926
 
0.2%
3.42 4913
 
0.5%
3.43 8450
 
0.8%
3.44 11439
 
1.1%
3.45 16923
1.7%
3.46 24204
2.4%
3.47 41912
4.1%
ValueCountFrequency (%)
3.72 275
 
< 0.1%
3.7 275
 
< 0.1%
3.69 253
 
< 0.1%
3.68 546
 
0.1%
3.67 264
 
< 0.1%
3.66 789
 
0.1%
3.65 3458
 
0.3%
3.64 4006
 
0.4%
3.63 10124
1.0%
3.62 19069
1.9%

multiple_values
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1020495 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1020495
100.0%

Length

2023-02-19T12:11:37.514802image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:37.787075image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring characters

ValueCountFrequency (%)
0 1020495
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1020495
100.0%

mark knight
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1013496 
1
 
6999

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1013496
99.3%
1 6999
 
0.7%

Length

2023-02-19T12:11:37.983550image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:38.401547image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1013496
99.3%
1 6999
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0 1013496
99.3%
1 6999
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1013496
99.3%
1 6999
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1013496
99.3%
1 6999
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1013496
99.3%
1 6999
 
0.7%

cannis holder
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1016712 
1
 
3783

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1016712
99.6%
1 3783
 
0.4%

Length

2023-02-19T12:11:38.777089image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:39.215508image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1016712
99.6%
1 3783
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 1016712
99.6%
1 3783
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1016712
99.6%
1 3783
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1016712
99.6%
1 3783
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1016712
99.6%
1 3783
 
0.4%

jay chapman
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1019163 
1
 
1332

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1019163
99.9%
1 1332
 
0.1%

Length

2023-02-19T12:11:39.602477image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:39.984516image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1019163
99.9%
1 1332
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 1019163
99.9%
1 1332
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1019163
99.9%
1 1332
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1019163
99.9%
1 1332
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1019163
99.9%
1 1332
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1019168 
1
 
1327

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1019168
99.9%
1 1327
 
0.1%

Length

2023-02-19T12:11:40.226864image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:40.531051image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1019168
99.9%
1 1327
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 1019168
99.9%
1 1327
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1019168
99.9%
1 1327
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1019168
99.9%
1 1327
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1019168
99.9%
1 1327
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1019959 
1
 
536

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1019959
99.9%
1 536
 
0.1%

Length

2023-02-19T12:11:40.773404image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:41.362623image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1019959
99.9%
1 536
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 1019959
99.9%
1 536
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1019959
99.9%
1 536
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1019959
99.9%
1 536
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1019959
99.9%
1 536
 
0.1%

maggie binkley
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1017497 
1
 
2998

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1017497
99.7%
1 2998
 
0.3%

Length

2023-02-19T12:11:41.611942image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:42.480386image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1017497
99.7%
1 2998
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 1017497
99.7%
1 2998
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1017497
99.7%
1 2998
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1017497
99.7%
1 2998
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1017497
99.7%
1 2998
 
0.3%

shah rukh khan
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1018917 
1
 
1578

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1018917
99.8%
1 1578
 
0.2%

Length

2023-02-19T12:11:42.992019image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:43.293213image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1018917
99.8%
1 1578
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 1018917
99.8%
1 1578
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1018917
99.8%
1 1578
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1018917
99.8%
1 1578
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1018917
99.8%
1 1578
 
0.2%

gene autry
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1018905 
1
 
1590

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1018905
99.8%
1 1590
 
0.2%

Length

2023-02-19T12:11:43.502653image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:43.698148image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1018905
99.8%
1 1590
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 1018905
99.8%
1 1590
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1018905
99.8%
1 1590
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1018905
99.8%
1 1590
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1018905
99.8%
1 1590
 
0.2%

akshay kumar
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1019169 
1
 
1326

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1019169
99.9%
1 1326
 
0.1%

Length

2023-02-19T12:11:43.879467image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:44.102888image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1019169
99.9%
1 1326
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 1019169
99.9%
1 1326
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1019169
99.9%
1 1326
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1019169
99.9%
1 1326
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1019169
99.9%
1 1326
 
0.1%

nicolas cage
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1019090 
1
 
1405

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1019090
99.9%
1 1405
 
0.1%

Length

2023-02-19T12:11:44.290386image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:44.536726image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1019090
99.9%
1 1405
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 1019090
99.9%
1 1405
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1019090
99.9%
1 1405
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1019090
99.9%
1 1405
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1019090
99.9%
1 1405
 
0.1%

united states
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
795073 
1
225422 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 795073
77.9%
1 225422
 
22.1%

Length

2023-02-19T12:11:44.740183image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:44.968085image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 795073
77.9%
1 225422
 
22.1%

Most occurring characters

ValueCountFrequency (%)
0 795073
77.9%
1 225422
 
22.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 795073
77.9%
1 225422
 
22.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 795073
77.9%
1 225422
 
22.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 795073
77.9%
1 225422
 
22.1%

india
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
962406 
1
 
58089

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 962406
94.3%
1 58089
 
5.7%

Length

2023-02-19T12:11:45.169482image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:45.970400image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 962406
94.3%
1 58089
 
5.7%

Most occurring characters

ValueCountFrequency (%)
0 962406
94.3%
1 58089
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 962406
94.3%
1 58089
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 962406
94.3%
1 58089
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 962406
94.3%
1 58089
 
5.7%

diftiempo
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct120
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.575752
Minimum-25
Maximum94
Zeros27412
Zeros (%)2.7%
Negative752171
Negative (%)73.7%
Memory size7.8 MiB
2023-02-19T12:11:46.244665image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum-25
5-th percentile-19
Q1-13
median-7
Q30
95-th percentile28
Maximum94
Range119
Interquartile range (IQR)13

Descriptive statistics

Standard deviation15.956021
Coefficient of variation (CV)-4.4622839
Kurtosis7.3064171
Mean-3.575752
Median Absolute Deviation (MAD)7
Skewness2.3917174
Sum-3649037
Variance254.59459
MonotonicityNot monotonic
2023-02-19T12:11:46.641606image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4 45136
 
4.4%
-5 42414
 
4.2%
-13 41696
 
4.1%
-12 41584
 
4.1%
-14 41425
 
4.1%
-3 40469
 
4.0%
-11 40388
 
4.0%
-15 40096
 
3.9%
-10 38565
 
3.8%
-16 38055
 
3.7%
Other values (110) 610667
59.8%
ValueCountFrequency (%)
-25 783
 
0.1%
-24 1692
 
0.2%
-23 2694
 
0.3%
-22 7219
 
0.7%
-21 15730
1.5%
-20 21048
2.1%
-19 24259
2.4%
-18 28051
2.7%
-17 32159
3.2%
-16 38055
3.7%
ValueCountFrequency (%)
94 15
 
< 0.1%
93 24
 
< 0.1%
92 29
< 0.1%
91 22
 
< 0.1%
90 20
 
< 0.1%
89 19
 
< 0.1%
88 11
 
< 0.1%
87 17
 
< 0.1%
86 23
 
< 0.1%
85 71
< 0.1%

13+
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
931184 
1
 
89311

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 931184
91.2%
1 89311
 
8.8%

Length

2023-02-19T12:11:46.960488image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:47.219794image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 931184
91.2%
1 89311
 
8.8%

Most occurring characters

ValueCountFrequency (%)
0 931184
91.2%
1 89311
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 931184
91.2%
1 89311
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 931184
91.2%
1 89311
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 931184
91.2%
1 89311
 
8.8%

16
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1020495 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1020495
100.0%

Length

2023-02-19T12:11:47.408290image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:47.577440image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring characters

ValueCountFrequency (%)
0 1020495
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1020495
100.0%

16+
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
949494 
1
 
71001

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 949494
93.0%
1 71001
 
7.0%

Length

2023-02-19T12:11:47.755480image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:48.041712image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 949494
93.0%
1 71001
 
7.0%

Most occurring characters

ValueCountFrequency (%)
0 949494
93.0%
1 71001
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 949494
93.0%
1 71001
 
7.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 949494
93.0%
1 71001
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 949494
93.0%
1 71001
 
7.0%

18+
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
969494 
1
 
51001

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 969494
95.0%
1 51001
 
5.0%

Length

2023-02-19T12:11:48.243173image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:48.511458image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 969494
95.0%
1 51001
 
5.0%

Most occurring characters

ValueCountFrequency (%)
0 969494
95.0%
1 51001
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 969494
95.0%
1 51001
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 969494
95.0%
1 51001
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 969494
95.0%
1 51001
 
5.0%

7+
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1001429 
1
 
19066

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1001429
98.1%
1 19066
 
1.9%

Length

2023-02-19T12:11:48.774779image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:49.037076image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1001429
98.1%
1 19066
 
1.9%

Most occurring characters

ValueCountFrequency (%)
0 1001429
98.1%
1 19066
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1001429
98.1%
1 19066
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1001429
98.1%
1 19066
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1001429
98.1%
1 19066
 
1.9%

ages_16_
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1020495 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1020495
100.0%

Length

2023-02-19T12:11:49.290916image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:49.689886image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring characters

ValueCountFrequency (%)
0 1020495
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1020495
100.0%

ages_18_
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1020235 
1
 
260

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1020235
> 99.9%
1 260
 
< 0.1%

Length

2023-02-19T12:11:49.950193image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:50.680162image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1020235
> 99.9%
1 260
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 1020235
> 99.9%
1 260
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1020235
> 99.9%
1 260
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1020235
> 99.9%
1 260
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1020235
> 99.9%
1 260
 
< 0.1%

all
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
962740 
1
 
57755

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 962740
94.3%
1 57755
 
5.7%

Length

2023-02-19T12:11:50.894587image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:51.165893image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 962740
94.3%
1 57755
 
5.7%

Most occurring characters

ValueCountFrequency (%)
0 962740
94.3%
1 57755
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 962740
94.3%
1 57755
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 962740
94.3%
1 57755
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 962740
94.3%
1 57755
 
5.7%

all_ages
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1020495 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1020495
100.0%

Length

2023-02-19T12:11:51.428735image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:51.664106image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring characters

ValueCountFrequency (%)
0 1020495
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1020495
100.0%

g
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
952133 
1
 
68362

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 952133
93.3%
1 68362
 
6.7%

Length

2023-02-19T12:11:51.901471image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:52.198190image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 952133
93.3%
1 68362
 
6.7%

Most occurring characters

ValueCountFrequency (%)
0 952133
93.3%
1 68362
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 952133
93.3%
1 68362
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 952133
93.3%
1 68362
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 952133
93.3%
1 68362
 
6.7%

nc-17
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1020227 
1
 
268

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1020227
> 99.9%
1 268
 
< 0.1%

Length

2023-02-19T12:11:52.368737image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:52.561135image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1020227
> 99.9%
1 268
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 1020227
> 99.9%
1 268
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1020227
> 99.9%
1 268
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1020227
> 99.9%
1 268
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1020227
> 99.9%
1 268
 
< 0.1%

not rated
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1020495 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1020495
100.0%

Length

2023-02-19T12:11:52.768425image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:53.111033image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring characters

ValueCountFrequency (%)
0 1020495
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1020495
100.0%

not_rate
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1020495 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1020495
100.0%

Length

2023-02-19T12:11:53.297527image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:53.529908image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring characters

ValueCountFrequency (%)
0 1020495
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1020495
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1020495
100.0%

nr
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1008283 
1
 
12212

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1008283
98.8%
1 12212
 
1.2%

Length

2023-02-19T12:11:53.718403image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:53.965769image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1008283
98.8%
1 12212
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 1008283
98.8%
1 12212
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1008283
98.8%
1 12212
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1008283
98.8%
1 12212
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1008283
98.8%
1 12212
 
1.2%

pg
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
976019 
1
 
44476

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 976019
95.6%
1 44476
 
4.4%

Length

2023-02-19T12:11:54.170223image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:54.443143image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 976019
95.6%
1 44476
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 976019
95.6%
1 44476
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 976019
95.6%
1 44476
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 976019
95.6%
1 44476
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 976019
95.6%
1 44476
 
4.4%

pg-13
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
969776 
1
 
50719

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 969776
95.0%
1 50719
 
5.0%

Length

2023-02-19T12:11:54.885475image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:55.196157image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 969776
95.0%
1 50719
 
5.0%

Most occurring characters

ValueCountFrequency (%)
0 969776
95.0%
1 50719
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 969776
95.0%
1 50719
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 969776
95.0%
1 50719
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 969776
95.0%
1 50719
 
5.0%

r
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
936434 
1
 
84061

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 936434
91.8%
1 84061
 
8.2%

Length

2023-02-19T12:11:55.388643image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:55.641966image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 936434
91.8%
1 84061
 
8.2%

Most occurring characters

ValueCountFrequency (%)
0 936434
91.8%
1 84061
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 936434
91.8%
1 84061
 
8.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 936434
91.8%
1 84061
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 936434
91.8%
1 84061
 
8.2%

tv-14
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
873267 
1
147228 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 873267
85.6%
1 147228
 
14.4%

Length

2023-02-19T12:11:55.832454image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:56.086866image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 873267
85.6%
1 147228
 
14.4%

Most occurring characters

ValueCountFrequency (%)
0 873267
85.6%
1 147228
 
14.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 873267
85.6%
1 147228
 
14.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 873267
85.6%
1 147228
 
14.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 873267
85.6%
1 147228
 
14.4%

tv-g
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
988222 
1
 
32273

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 988222
96.8%
1 32273
 
3.2%

Length

2023-02-19T12:11:56.292075image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:56.504440image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 988222
96.8%
1 32273
 
3.2%

Most occurring characters

ValueCountFrequency (%)
0 988222
96.8%
1 32273
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 988222
96.8%
1 32273
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 988222
96.8%
1 32273
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 988222
96.8%
1 32273
 
3.2%

tv-ma
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
853732 
1
166763 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 853732
83.7%
1 166763
 
16.3%

Length

2023-02-19T12:11:56.648055image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:56.874449image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 853732
83.7%
1 166763
 
16.3%

Most occurring characters

ValueCountFrequency (%)
0 853732
83.7%
1 166763
 
16.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 853732
83.7%
1 166763
 
16.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 853732
83.7%
1 166763
 
16.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 853732
83.7%
1 166763
 
16.3%

tv-nr
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1015266 
1
 
5229

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 1015266
99.5%
1 5229
 
0.5%

Length

2023-02-19T12:11:57.069927image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:57.317265image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1015266
99.5%
1 5229
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 1015266
99.5%
1 5229
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1015266
99.5%
1 5229
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1015266
99.5%
1 5229
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1015266
99.5%
1 5229
 
0.5%

tv-pg
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
947528 
1
 
72967

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 947528
92.8%
1 72967
 
7.2%

Length

2023-02-19T12:11:57.510748image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:57.762084image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 947528
92.8%
1 72967
 
7.2%

Most occurring characters

ValueCountFrequency (%)
0 947528
92.8%
1 72967
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 947528
92.8%
1 72967
 
7.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 947528
92.8%
1 72967
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 947528
92.8%
1 72967
 
7.2%

tv-y
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1000202 
1
 
20293

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1000202
98.0%
1 20293
 
2.0%

Length

2023-02-19T12:11:57.961582image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:58.290753image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1000202
98.0%
1 20293
 
2.0%

Most occurring characters

ValueCountFrequency (%)
0 1000202
98.0%
1 20293
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1000202
98.0%
1 20293
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1000202
98.0%
1 20293
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1000202
98.0%
1 20293
 
2.0%

tv-y7
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
995958 
1
 
24537

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 995958
97.6%
1 24537
 
2.4%

Length

2023-02-19T12:11:58.486744image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:58.750041image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 995958
97.6%
1 24537
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 995958
97.6%
1 24537
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 995958
97.6%
1 24537
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 995958
97.6%
1 24537
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 995958
97.6%
1 24537
 
2.4%

tv-y7-fv
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1019440 
1
 
1055

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1019440
99.9%
1 1055
 
0.1%

Length

2023-02-19T12:11:58.930555image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:59.159943image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1019440
99.9%
1 1055
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 1019440
99.9%
1 1055
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1019440
99.9%
1 1055
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1019440
99.9%
1 1055
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1019440
99.9%
1 1055
 
0.1%

unrated
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1019110 
1
 
1385

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1019110
99.9%
1 1385
 
0.1%

Length

2023-02-19T12:11:59.347442image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:11:59.683542image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1019110
99.9%
1 1385
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 1019110
99.9%
1 1385
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1019110
99.9%
1 1385
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1019110
99.9%
1 1385
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1019110
99.9%
1 1385
 
0.1%

ur
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
1020222 
1
 
273

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1020222
> 99.9%
1 273
 
< 0.1%

Length

2023-02-19T12:11:59.901473image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:12:00.130860image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1020222
> 99.9%
1 273
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 1020222
> 99.9%
1 273
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1020222
> 99.9%
1 273
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1020222
> 99.9%
1 273
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1020222
> 99.9%
1 273
 
< 0.1%

drama
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
857873 
1
162622 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 857873
84.1%
1 162622
 
15.9%

Length

2023-02-19T12:12:00.311378image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:12:00.504859image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 857873
84.1%
1 162622
 
15.9%

Most occurring characters

ValueCountFrequency (%)
0 857873
84.1%
1 162622
 
15.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 857873
84.1%
1 162622
 
15.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 857873
84.1%
1 162622
 
15.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 857873
84.1%
1 162622
 
15.9%

comedy
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
941841 
1
 
78654

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 941841
92.3%
1 78654
 
7.7%

Length

2023-02-19T12:12:00.708847image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:12:01.050450image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 941841
92.3%
1 78654
 
7.7%

Most occurring characters

ValueCountFrequency (%)
0 941841
92.3%
1 78654
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 941841
92.3%
1 78654
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 941841
92.3%
1 78654
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 941841
92.3%
1 78654
 
7.7%

documentaries
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
947836 
1
 
72659

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 947836
92.9%
1 72659
 
7.1%

Length

2023-02-19T12:12:01.464406image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:12:01.988067image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 947836
92.9%
1 72659
 
7.1%

Most occurring characters

ValueCountFrequency (%)
0 947836
92.9%
1 72659
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 947836
92.9%
1 72659
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 947836
92.9%
1 72659
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 947836
92.9%
1 72659
 
7.1%

kids
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
969538 
1
 
50957

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 969538
95.0%
1 50957
 
5.0%

Length

2023-02-19T12:12:02.232408image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:12:02.548560image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 969538
95.0%
1 50957
 
5.0%

Most occurring characters

ValueCountFrequency (%)
0 969538
95.0%
1 50957
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 969538
95.0%
1 50957
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 969538
95.0%
1 50957
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 969538
95.0%
1 50957
 
5.0%

horror, suspense
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
992413 
1
 
28082

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 992413
97.2%
1 28082
 
2.8%

Length

2023-02-19T12:12:02.964278image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:12:03.227575image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 992413
97.2%
1 28082
 
2.8%

Most occurring characters

ValueCountFrequency (%)
0 992413
97.2%
1 28082
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 992413
97.2%
1 28082
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 992413
97.2%
1 28082
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 992413
97.2%
1 28082
 
2.8%

amazon
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
593544 
1
426951 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 593544
58.2%
1 426951
41.8%

Length

2023-02-19T12:12:03.430392image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:12:04.213589image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 593544
58.2%
1 426951
41.8%

Most occurring characters

ValueCountFrequency (%)
0 593544
58.2%
1 426951
41.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 593544
58.2%
1 426951
41.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 593544
58.2%
1 426951
41.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 593544
58.2%
1 426951
41.8%

netflix
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
621825 
1
398670 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 621825
60.9%
1 398670
39.1%

Length

2023-02-19T12:12:04.413335image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:12:04.670655image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 621825
60.9%
1 398670
39.1%

Most occurring characters

ValueCountFrequency (%)
0 621825
60.9%
1 398670
39.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 621825
60.9%
1 398670
39.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 621825
60.9%
1 398670
39.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 621825
60.9%
1 398670
39.1%

hulu
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
888522 
1
131973 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 888522
87.1%
1 131973
 
12.9%

Length

2023-02-19T12:12:04.852170image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:12:05.192794image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 888522
87.1%
1 131973
 
12.9%

Most occurring characters

ValueCountFrequency (%)
0 888522
87.1%
1 131973
 
12.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 888522
87.1%
1 131973
 
12.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 888522
87.1%
1 131973
 
12.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 888522
87.1%
1 131973
 
12.9%

disney
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.8 MiB
0
957594 
1
 
62901

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1020495
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 957594
93.8%
1 62901
 
6.2%

Length

2023-02-19T12:12:05.462583image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-19T12:12:05.656822image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 957594
93.8%
1 62901
 
6.2%

Most occurring characters

ValueCountFrequency (%)
0 957594
93.8%
1 62901
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1020495
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 957594
93.8%
1 62901
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1020495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 957594
93.8%
1 62901
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 957594
93.8%
1 62901
 
6.2%

Interactions

2023-02-19T12:11:00.386831image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:43.687022image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:47.175458image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:50.618171image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:53.598508image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:57.184946image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:11:00.837622image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:44.348253image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:47.819246image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:51.077551image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:54.050299image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:57.638662image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:11:01.348293image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:44.864871image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:48.305682image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:51.518372image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:54.820394image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:58.381191image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:11:01.844966image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:45.378527image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:49.079127image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:51.973155image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:55.329142image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:58.865296image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:11:02.352120image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:45.927060image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:49.648224image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:52.546839image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:55.918325image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:59.323597image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:11:02.943605image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:46.580052image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:50.125490image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:53.036043image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:56.501767image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-02-19T12:10:59.913533image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Correlations

2023-02-19T12:12:06.040794image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Auto

The auto setting is an interpretable pairwise column metric of the following mapping:
  • Variable_type-Variable_type : Method, Range
  • Categorical-Categorical : Cramer's V, [0,1]
  • Numerical-Categorical : Cramer's V, [0,1] (using a discretized numerical column)
  • Numerical-Numerical : Spearman's ρ, [-1,1]
The number of bins used in the discretization for the Numerical-Categorical column pair can be changed using config.correlations["auto"].n_bins. The number of bins affects the granularity of the association you wish to measure.

This configuration uses the recommended metric for each pair of columns.
2023-02-19T12:12:07.123438image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2023-02-19T12:12:08.587784image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2023-02-19T12:12:10.332669image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2023-02-19T12:12:11.597828image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2023-02-19T12:12:12.875125image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2023-02-19T12:11:04.559801image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-02-19T12:11:14.545179image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

userIdscoreidtitleyearduration_intduration_typescoredmultiple_valuesmark knightcannis holderjay chapmanmoonbug entertainmentarthur van merwijkmaggie binkleyshah rukh khangene autryakshay kumarnicolas cageunited statesindiadiftiempo13+1616+18+7+ages_16_ages_18_allall_agesgnc-17not ratednot_ratenrpgpg-13rtv-14tv-gtv-matv-nrtv-pgtv-ytv-y7tv-y7-fvunratedurdramacomedydocumentarieskidshorror, suspenseamazonnetflixhuludisney
01324.0as3004bookaboo uk20091season3.430000000000000-7000000000000000000001000000000101000
11504.0as3004bookaboo uk20091season3.430000000000000-10000000000000000000001000000000101000
219444.5as3004bookaboo uk20091season3.430000000000000-4000000000000000000001000000000101000
321911.5as3004bookaboo uk20091season3.4300000000000007000000000000000000001000000000101000
426392.5as3004bookaboo uk20091season3.4300000000000001000000000000000000001000000000101000
527872.5as3004bookaboo uk20091season3.430000000000000-4000000000000000000001000000000101000
630285.0as3004bookaboo uk20091season3.4300000000000008000000000000000000001000000000101000
733473.5as3004bookaboo uk20091season3.430000000000000-1000000000000000000001000000000101000
835193.5as3004bookaboo uk20091season3.4300000000000007000000000000000000001000000000101000
939102.5as3004bookaboo uk20091season3.430000000000000-1000000000000000000001000000000101000
userIdscoreidtitleyearduration_intduration_typescoredmultiple_valuesmark knightcannis holderjay chapmanmoonbug entertainmentarthur van merwijkmaggie binkleyshah rukh khangene autryakshay kumarnicolas cageunited statesindiadiftiempo13+1616+18+7+ages_16_ages_18_allall_agesgnc-17not ratednot_ratenrpgpg-13rtv-14tv-gtv-matv-nrtv-pgtv-ytv-y7tv-y7-fvunratedurdramacomedydocumentarieskidshorror, suspenseamazonnetflixhuludisney
10204851214214.5hs986moesha19966season3.63000000000001012000000000000000000000100000000000010
10204861221794.5hs986moesha19966season3.63000000000001021000000000000000000000100000000000010
10204871222974.0hs986moesha19966season3.6300000000000107000000000000000000000100000000000010
10204881226422.0hs986moesha19966season3.6300000000000104000000000000000000000100000000000010
10204891228384.0hs986moesha19966season3.63000000000001013000000000000000000000100000000000010
10204901228903.5hs986moesha19966season3.63000000000001013000000000000000000000100000000000010
10204911234841.5hs986moesha19966season3.63000000000001019000000000000000000000100000000000010
10204921238003.5hs986moesha19966season3.63000000000001011000000000000000000000100000000000010
10204931239134.5hs986moesha19966season3.63000000000001021000000000000000000000100000000000010
10204941239233.0hs986moesha19966season3.6300000000000107000000000000000000000100000000000010

Duplicate rows

Most frequently occurring

userIdscoreidtitleyearduration_intduration_typescoredmultiple_valuesmark knightcannis holderjay chapmanmoonbug entertainmentarthur van merwijkmaggie binkleyshah rukh khangene autryakshay kumarnicolas cageunited statesindiadiftiempo13+1616+18+7+ages_16_ages_18_allall_agesgnc-17not ratednot_ratenrpgpg-13rtv-14tv-gtv-matv-nrtv-pgtv-ytv-y7tv-y7-fvunratedurdramacomedydocumentarieskidshorror, suspenseamazonnetflixhuludisney# duplicates
6858293.0ns1642sugar rush christmas20202season3.520000000000010-50000000000000000010000000000000001003
454352333.0ns8189the amityville horror200589min3.580000000000010100000000000000000100000000000000001003
601458112.5as7207cartoon classics - vol. 1: 25 favorite cartoons - 3 hours2017175min3.580000000000000-11000000000000000000000000000000010003
02293.0ns2839ugly delicious20202season3.570000000000010-180000000000000000000100000000000001002
12294.0as2191hooplakidz nursery rhyme time - part 2201917min3.510000000000000-170000000100000000000000000000001010002
23624.0as34556 minutes of yoga by the ocean20166min3.510100000000000-170000000100000000000000000000000010002
33983.0as1349penguin (tamil)2020132min3.540000000000000-160010000000000000000000000001000010002
44292.5as1676midnight rain for sleep black screen 4 hours2017240min3.510100000000000-30000000100000000000000000000000010002
54293.0ns5879mike epps: don't take it personal201560min3.520000000000010-10000000000000000000100000000100001002
66742.5as291top gear: from a-z20151season3.55000000000000010000000000000000010000000000000010002